Typically, performance of a partitioned computing system including multiple partitions is measured in terms of usage of its resources, such as central processing unit (CPU), input/output (I/O), memory and the like. Peak usage of a partitioned computing system's resources in a datacenter usually happens at different times and many times they can be random and unpredictable. An increase or decrease in the usage of a partitioned computing system's resource can affect its performance and needs to be managed reliably for performance improvements, i.e., hardware resources of the partitioned computing system need to be managed to improve performance.
Very often, this assured reliability and management of resources on the partitioned computing system are governed by service level agreements (SLAs). For example, a user may assign the resources to one or more partitions based on SLAs, which may not require all of the assigned resources to run the applications. This can result in underutilizing the assigned resources and can also result in risk of resource utilization being low. In contrast, the user can assign less than required resources to the one or more partitions in the partitioned computing system, which can result in risk of resource utilization being high and can significantly affect performance.